Bridging Data and Decision-Making: Data Visualization Techniques with R
Nnamdi Azikwe University
Data Types Contd
Categorical
Why Data Visualization Matters
Humans process visuals 60,000x faster than text
Visuals simplify complex data
Helps identify trends, outliers, and patterns
Supports data-driven decisions
Real-World Example:
COVID-19 dashboards helped governments track and respond to infection spikes and vaccinations.
Bridging the Gap Between Data and Decisions
Problem: Data is abundant, but insights are scarce.
Solution: Visualization bridges the gap between raw data and strategic action.
Outcome: Simplifies storytelling and supports real-time decisions.
What is R and Why Use It?
R
Free and open-source statistical language
Used in academia and business
Integrates data wrangling, analysis, and visualization
Key Visualization Packages:
ggplot2
plotly
shiny
Understanding Visualization Types
| Line Chart |
Trends over time |
| Bar Chart |
Comparing categories |
| Scatter Plot |
Correlations, relationships |
| Maps |
Geospatial data |
| Dashboard |
Monitoring KPIs in real-time |
Tip: Choose simplicity and clarity over complexity.
Academic Use Case – Education Access
Dataset: World Bank (Literacy vs Internet Access)
Visualization: Scatter plot showing socio-economic development.
Insight: Nigeria lags behind Kenya and Egypt in internet penetration despite comparable literacy rates.
